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D-Index & Metrics

Biology and Biochemistry

D-Index
60
Citations
25374
World Ranking
11674
National Ranking
5022

Overview

David H. Mathews is affiliated with the University of Rochester Medical Center in the United States. Their research primarily focuses on the field of Biochemistry, Genetics and Molecular Biology, with a particular emphasis on Molecular Biology. Other subfields they have contributed to include Cardiology and Cardiovascular Medicine, Genetics, Infectious Diseases, and Epidemiology.

The main topics of their work cover areas such as RNA and protein synthesis mechanisms, RNA modifications and cancer, RNA research and splicing, and DNA and nucleic acid chemistry. Additional topics include Genomics and Phylogenetic Studies, RNA interference and gene delivery, as well as viral infections and immunology research.

Recent research papers authored or coauthored by David H. Mathews include the following:

  • Algorithm for optimized mRNA design improves stability and immunogenicity, 2023, Nature
  • Secondary structure prediction for RNA sequences including N6-methyladenosine, 2022, Nature Communications
  • LinearPartition: linear-time approximation of RNA folding partition function and base-pairing probabilities, 2020, Bioinformatics
  • Deep learning models for RNA secondary structure prediction (probably) do not generalize across families, 2022, Bioinformatics
  • Arginine Forks Are a Widespread Motif to Recognize Phosphate Backbones and Guanine Nucleobases in the RNA Major Groove, 2020, Journal of the American Chemical Society

Throughout their career, David H. Mathews has frequently collaborated with several coauthors. The most frequent collaborators include:

  • Liang Huang
  • He Zhang
  • Sizhen Li
  • Liang Zhang
  • Ryszard Kierzek

Their work has been published extensively in several scientific venues. The most common venues for their publications are:

  • bioRxiv (Cold Spring Harbor Laboratory)
  • Journal of Molecular Biology
  • Nucleic Acids Research
  • Zenodo (CERN European Organization for Nuclear Research)
  • arXiv (Cornell University)

Best Publications

  • Expanded sequence dependence of thermodynamic parameters improves prediction of RNA secondary structure.

    David H. Mathews;Jeffrey Sabina;Michael Zuker;Douglas H. Turner

  • Incorporating chemical modification constraints into a dynamic programming algorithm for prediction of RNA secondary structure

    David H. Mathews;Matthew D. Disney;Jessica L. Childs;Susan J. Schroeder

  • RNAstructure: software for RNA secondary structure prediction and analysis

    Jessica S Reuter;David H Mathews

  • Algorithms and Thermodynamics for RNA Secondary Structure Prediction: A Practical Guide

    M. Zuker;D. H. Mathews;D. H. Turner

  • Accurate SHAPE-directed RNA structure determination

    Katherine E. Deigan;Tian W. Li;David H. Mathews;Kevin M. Weeks

  • Coaxial Stacking of Helixes Enhances Binding of Oligoribonucleotides and Improves Predictions of RNA Folding

    Amy E. Walter;Douglas H. Turner;James Kim;Matthew H. Lyttle

  • NNDB: the nearest neighbor parameter database for predicting stability of nucleic acid secondary structure

    Douglas H. Turner;David H. Mathews

  • Prediction of RNA secondary structure by free energy minimization.

    David H Mathews;Douglas H Turner;Douglas H Turner

  • Dynalign: an algorithm for finding the secondary structure common to two RNA sequences.

    David H. Mathews;Douglas H. Turner

  • High-throughput SHAPE analysis reveals structures in HIV-1 genomic RNA strongly conserved across distinct biological states.

    Kevin A Wilkinson;Robert J Gorelick;Suzy M Vasa;Nicolas Guex

  • Using an RNA secondary structure partition function to determine confidence in base pairs predicted by free energy minimization

    David H. Mathews

  • RNAstructure: web servers for RNA secondary structure prediction and analysis

    Stanislav Bellaousov;Jessica S. Reuter;Matthew G. Seetin;David H. Mathews

  • FragSeq: transcriptome-wide RNA structure probing using high-throughput sequencing

    Jason G Underwood;Andrew V Uzilov;Sol Katzman;Courtney S Onodera

  • Accurate SHAPE-directed RNA secondary structure modeling, including pseudoknots

    Christine E. Hajdin;Stanislav Bellaousov;Wayne Huggins;Christopher W. Leonard

  • Predicting oligonucleotide affinity to nucleic acid targets.

    David H. Mathews;Mark E. Burkard;Susan M. Freier;Jacqueline R. Wyatt

  • Efficient parameter estimation for RNA secondary structure prediction

    Mirela Andronescu;Anne Condon;Holger H. Hoos;David H. Mathews

  • Detection of non-coding RNAs on the basis of predicted secondary structure formation free energy change

    Andrew V Uzilov;Joshua M Keegan;David H Mathews

  • Revolutions in RNA secondary structure prediction.

    David H. Mathews

  • Improved RNA secondary structure prediction by maximizing expected pair accuracy.

    Zhi John Lu;Jason W. Gloor;David H. Mathews

  • ProbKnot: fast prediction of RNA secondary structure including pseudoknots.

    Stanislav Bellaousov;David H. Mathews

Frequent Co-Authors

Douglas H. Turner
Douglas H. Turner University of Rochester
Liang Huang
Liang Huang Oregon State University
Gaurav Sharma
Gaurav Sharma University of Rochester
Kevin M. Weeks
Kevin M. Weeks University of North Carolina at Chapel Hill
Philip C. Bevilacqua
Philip C. Bevilacqua Pennsylvania State University
Ryszard Kierzek
Ryszard Kierzek Polish Academy of Sciences
Anne Condon
Anne Condon University of British Columbia
Robert A. Bambara
Robert A. Bambara University of Rochester
Lawrence G. Lum
Lawrence G. Lum University of Virginia
Eric M. Phizicky
Eric M. Phizicky University of Rochester

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